Abstract
Most life activities are finished by protein-protein interactions(PPI). So far, there have been many methods proposed for link prediction in the PPI network. However, these prediction methods only use single information. This paper proposes a novel algorithm to predict the potential interactions based on the topological and attribute similarity between proteins. This paper also studies the way of balancing attribute similarity and topological similarity. The experimental results on yeast PPI network show that the proposed algorithm has higher accuracy and good biometric characteristic.
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Acknowledgements
This research was supported in part by the Chinese National Natural Science Foundation under grant Nos. 61379066, 61379064, 61472344, 61301220, 61402395, Natural Science Foundation of Jiangsu Province under contracts BK20130452, BK20151314 and BK20140492, and Natural Science Foundation of Education Department of Jiangsu Province under contract 12KJB520019, 13KJB520026.
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Wu, QM., Liu, W., Hong, Hy., Chen, L. (2016). A Novel Link Prediction Algorithm Based on Spatial Mapping in PPI Network. In: Yin, H., et al. Intelligent Data Engineering and Automated Learning – IDEAL 2016. IDEAL 2016. Lecture Notes in Computer Science(), vol 9937. Springer, Cham. https://doi.org/10.1007/978-3-319-46257-8_12
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DOI: https://doi.org/10.1007/978-3-319-46257-8_12
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